55 references to DotProduct
Microsoft.ML.Core.Tests (1)
UnitTests\TestVBuffer.cs (1)
839
Assert.True(CompareNumbersWithTolerance(dot, VectorUtils.
DotProduct
(in a, in b), digitsOfPrecision: tol));
Microsoft.ML.KMeansClustering (6)
KMeansModelParameters.cs (1)
173
-2 * VectorUtils.
DotProduct
(in _centroids[i], in src) + _centroidL2s[i] + instanceL2);
KMeansPlusPlusTrainer.cs (5)
399
var distance = -2 * VectorUtils.
DotProduct
(in cursor.Features, in centroids[j])
642
MathUtils.Sqrt(newClusterL2 - 2 * VectorUtils.
DotProduct
(in newClusterFeatures, in oldClusterFeatures) + oldClusterL2);
720
Contracts.Assert(-2 * VectorUtils.
DotProduct
(in point, in clusters[j]) + clustersL2s[j] > bestWeight);
724
float weight = -2 * VectorUtils.
DotProduct
(in point, in clusters[j]) + clustersL2s[j];
1804
float distance = -2 * VectorUtils.
DotProduct
(in features, in centroids[j]) + centroidL2s[j];
Microsoft.ML.PCA (4)
PcaTrainer.cs (4)
463
_meanProjected[i] = VectorUtils.
DotProduct
(in _eigenVectors[i], in mean);
512
_meanProjected[i] = VectorUtils.
DotProduct
(in _eigenVectors[i], in _mean);
638
2 * VectorUtils.
DotProduct
(in mean, in src) + _norm2Mean;
647
float component = VectorUtils.
DotProduct
(in _eigenVectors[i], in src) - _meanProjected[i];
Microsoft.ML.StandardTrainers (44)
LdSvm\LdSvmModelParameters.cs (5)
254
score += Math.Tanh(_sigma * (VectorUtils.
DotProduct
(in _thetaPrime[current], in src) + _biasThetaPrime[current])) *
255
(VectorUtils.
DotProduct
(in _w[current], in src) + _biasW[current]);
256
childIndicator = VectorUtils.
DotProduct
(in _theta[current], in src) + _biasTheta[current];
259
score += Math.Tanh(_sigma * (VectorUtils.
DotProduct
(in _thetaPrime[current], in src) + _biasThetaPrime[current])) *
260
(VectorUtils.
DotProduct
(in _w[current], in src) + _biasW[current]);
LdSvm\LdSvmTrainer.cs (6)
212
tanhThetaTx[i] = (float)Math.Tanh(gamma * (VectorUtils.
DotProduct
(in feat, in theta[i]) + biasTheta[i]));
216
float tempGrad = pathWt[i] * localWt[i] * (VectorUtils.
DotProduct
(in feat, in w[i]) + biasW[i]);
241
tempSum += Math.Abs(VectorUtils.
DotProduct
(in s, in theta[thetaIdx]) + biasTheta[thetaIdx]);
324
var tanhDist = (float)Math.Tanh(gamma * (VectorUtils.
DotProduct
(in features, in theta[i]) + biasTheta[i]));
331
localWt[l] = (float)Math.Tanh(_options.Sigma * (VectorUtils.
DotProduct
(in features, in thetaPrime[l]) + biasThetaPrime[l]));
337
wDotX[l] = VectorUtils.
DotProduct
(in features, in w[l]) + biasW[l];
Optimizer\DifferentiableFunction.cs (4)
225
float dirDeriv = VectorUtils.
DotProduct
(in grad, in dir);
272
float dirDeriv = VectorUtils.
DotProduct
(in grad, in dir);
311
float dirDeriv = VectorUtils.
DotProduct
(in grad, in dir);
336
float dirDeriv = VectorUtils.
DotProduct
(in newGrad, in dir);
Optimizer\L1Optimizer.cs (7)
199
float dirDeriv = -VectorUtils.
DotProduct
(in _dir, in _steepestDescDir);
211
float unnormCos = VectorUtils.
DotProduct
(in _steepestDescDir, in _newX) - VectorUtils.
DotProduct
(in _steepestDescDir, in _x);
222
unnormCos = VectorUtils.
DotProduct
(in _steepestDescDir, in _newX) - VectorUtils.
DotProduct
(in _steepestDescDir, in _x);
242
unnormCos = VectorUtils.
DotProduct
(in _steepestDescDir, in _newX) - VectorUtils.
DotProduct
(in _steepestDescDir, in _x);
Optimizer\LineSearch.cs (3)
464
float d1 = VectorUtils.
DotProduct
(in x, in _c1);
465
float d2 = VectorUtils.
DotProduct
(in x, in _c2);
466
float d3 = VectorUtils.
DotProduct
(in x, in _c3);
Optimizer\Optimizer.cs (7)
261
alphas[i] = -VectorUtils.
DotProduct
(in _sList[i], in _dir) / _roList[i];
272
float yDotY = VectorUtils.
DotProduct
(in _yList[lastGoodRo], in _yList[lastGoodRo]);
279
float beta = VectorUtils.
DotProduct
(in _yList[i], in _dir) / _roList[i];
359
float ro = VectorUtils.
DotProduct
(in nextS, in nextY);
383
float dirDeriv = VectorUtils.
DotProduct
(in _dir, in _grad);
425
dirDeriv = VectorUtils.
DotProduct
(in _dir, in _newGrad);
499
dirDeriv = VectorUtils.
DotProduct
(in _dir, in _newGrad);
Optimizer\SgdOptimizer.cs (3)
314
public float Deriv => VectorUtils.
DotProduct
(in _dir, in _grad);
333
deriv = VectorUtils.
DotProduct
(in _dir, in _newGrad);
342
float newByOld = VectorUtils.
DotProduct
(in _newGrad, in _grad);
Standard\LinearModelParameters.cs (2)
269
return Bias + VectorUtils.
DotProduct
(in weights, in src);
272
return Bias + VectorUtils.
DotProduct
(in _weightsDense, in src);
Standard\LogisticRegression\MulticlassLogisticRegression.cs (1)
791
editor.Values[i] = Biases[i] + VectorUtils.
DotProduct
(in weights[i], in src);
Standard\Online\AveragedLinear.cs (1)
185
return (TotalBias + VectorUtils.
DotProduct
(in feat, in TotalWeights)) / (float)NumWeightUpdates;
Standard\Online\LinearSvm.cs (1)
258
=> Bias + VectorUtils.
DotProduct
(in feat, in Weights) * WeightsScale;
Standard\Online\OnlineLinear.cs (1)
237
=> Bias + VectorUtils.
DotProduct
(in feat, in Weights) * WeightsScale;
Standard\SdcaBinary.cs (3)
132
return VectorUtils.
DotProduct
(in weights, in features) + bias;
137
return VectorUtils.
DotProduct
(in weights, in features) * (float)scaling + bias;
319
return VectorUtils.
DotProduct
(in weights, in features) + bias;